Automatic Scoring System for Evaluating Comprehensive Answers using Key Features (ASCA)
N.Sivaranjani1, Amudha S2, Mary Linda I3
1N.Sivaranjani, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
2Amudha S, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
3Mary Linda I, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
Manuscript received on 13 September 2019 | Revised Manuscript received on 22 September 2019 | Manuscript Published on 10 October 2019 | PP: 213-216 | Volume-8 Issue-6S2, August 2019 | Retrieval Number: F10570886S219/19©BEIESP | DOI: 10.35940/ijeat.F1057.0886S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Automatic evaluation of learner’s skills is the hot research area in the field of Machine learning. The key idea behind automatic scoring system for evaluating students answer is to reduce the time for instructors in evaluating the test paper and to make the scores consistent. This paper not only aims to evaluate the answer and also takes care of malpractice by implementing plagiarism and also redundant sentences. Redundant sentences may lead to erroneous grades. Experimental results show that our system shows better grading than the existing and also has higher match with the human judgment, especially for the answer that has higher similarity with answer key.
Keywords: Automatic Scoring, Similarity Measure, Sentecne Ordering.
Scope of the Article: Expert Systems